[HTML][HTML] Machine learning algorithms for monitoring pavement performance

S Cano-Ortiz, P Pascual-Muñoz… - Automation in …, 2022 - Elsevier
This work introduces the need to develop competitive, low-cost and applicable technologies
to real roads to detect the asphalt condition by means of Machine Learning (ML) algorithms …

Comparison of histogram-based gradient boosting classification machine, random Forest, and deep convolutional neural network for pavement raveling severity …

H Nhat-Duc, T Van-Duc - Automation in Construction, 2023 - Elsevier
Raveling is a widely encountered defect found in asphalt pavements. Raveling deteriorates
riding safety and accelerates the development of other pavement defects. Therefore, timely …

[PDF][PDF] Automated pavement distress detection, classification and measurement: A review

B Benmhahe, JA Chentoufi - International Journal of …, 2021 - pdfs.semanticscholar.org
Road surface distress is an unavoidable situation due to age, vehicles overloading,
temperature changes, etc. In the beginning, pavement maintenance actions took only place …

PotSpot: Participatory sensing based monitoring system for pothole detection using deep learning

S Patra, AI Middya, S Roy - Multimedia Tools and Applications, 2021 - Springer
Proper maintenance of roads is an extremely complex task and also an important issue all
over the world. One of the most critical road monitoring and maintenance activities is the …

Surface concrete cracks detection and segmentation using transfer learning and multi-resolution image processing

M Iraniparast, S Ranjbar, M Rahai, FM Nejad - Structures, 2023 - Elsevier
Surface crack detection must be precise and efficient for the structural health monitoring
(SHM) of concrete structures. The traditional techniques of crack detection entail human …

Automatic detection of cracks in asphalt pavement using deep learning to overcome weaknesses in images and GIS visualization

P Chun, T Yamane, Y Tsuzuki - Applied Sciences, 2021 - mdpi.com
Featured Application This technology can contribute to improving the efficiency and
accuracy of pavement inspection. Abstract The crack ratio is one of the indices used to …

Effective medium crack classification on laboratory concrete specimens via competitive machine learning

JA Guzmán-Torres, MZ Naser, FJ Domínguez-Mota - Structures, 2022 - Elsevier
With the advent rise of automation, it is now possible to trace and detect damage in structural
systems with ease. Unfortunately, existing inspection methods continue to suffer on a …

A novel approach for detection of pavement crack and sealed crack using image processing and salp swarm algorithm optimized machine learning

ND Hoang, TC Huynh, XL Tran… - Advances in Civil …, 2022 - Wiley Online Library
During the phase of periodic survey, sealed crack and crack in asphalt pavement surface
should be detected accurately. Moreover, the capability of identifying these two defects can …

Pavement raveling inspection using a new image texture-based feature set and artificial intelligence

A Nasertork, S Ranjbar, M Rahai, FM Nejad - Advanced Engineering …, 2024 - Elsevier
Enhancing pavement distress inspection is crucial within a pavement management system.
Recognizing the advantages of automated pavement condition inspection, considerable …

[HTML][HTML] Evaluation and optimisation of pre-trained CNN models for asphalt pavement crack detection and classification

S Matarneh, F Elghaish, FP Rahimian… - Automation in …, 2024 - Elsevier
This study explored the performance of ten pre-trained CNN architectures in detecting and
classifying asphalt pavement cracks from images. A comparison of eight optimisation …